The evolution from wireless based voice only communication networks to wireless based voice and data communication networks has resulted in the development of general packet radio service (GPRS) and enhanced data rates for the global system for mobile communications (GSM) standards. Although speech still remains the dominant service by many cellular service providers, existing systems are being upgraded to provide greater support for data communication via the radio interface.
The GSM standard, for example, provides data services with bit rates up to 14.4 kbps for circuit-switched data and up to 22.8 kbps for packet based (non-circuit switched) data. For GSM, higher bit rates may be achieved utilizing technological advancements such as high-speed circuit-switched data (HSCSD) technology and general packet radio service (GPRS) technology, which are based on the original gaussian minimum shift keying (GMSK) modulation scheme employed by GSM. In eight-state phase shift keying (8PSK), there are eight possible states that a signal can transition to at any time. 8PSK is a variation of PSK and has a symbol rate that is one third of the bit rate. Minimum Shift Keying (MSK) is used in the GSM cellular standard. Frequency Shift Keying (FSK) and MSK produce constant envelope carrier signals, which have no amplitude variations, a desirable characteristic for improving power efficiency of transmitters. In practice, waveforms are filtered with a gaussian filter, resulting in a narrow spectrum and no time domain overshoot. MSK with a gaussian filter is termed GMSK. GMSK is a spectrally efficient modulation scheme and is useful in mobile radio systems. GMSK has a constant envelope, spectral efficiency, good bit error rate (BER) performance, and is self-synchronizing.
Enhanced data for global evolution (EDGE) provides an enhancement to GPRS, which leverages a new modulation scheme along with various coding and radio link enhancements to provide much higher bit rates and capacity than GPRS. Due to the higher bit rates and the need to adapt the data protection to the channel and link quality, the EDGE radio link control (RLC) protocol is somewhat different from the corresponding GPRS protocol. EDGE is a 3G technology that delivers broadband-like data speeds to mobile devices. It allows consumers to connect to the Internet and to send and receive data, including digital images, web pages and photographs, three times faster than possible with an ordinary GSM and or GPRS networks. EDGE enables GSM operators to offer higher-speed mobile-data access, serve more mobile-data customers, and free up GSM network capacity to accommodate additional voice traffic.
In some conventional receivers, improvements may require extensive system modifications that may be very costly and, in some cases, may even be impractical. Determining the right approach to achieve design improvements may depend on the optimization of a receiver system to a particular modulation type and/or to the various kinds of noises that may be introduced by a transmission channel. For example, the optimization of a receiver system may be based on whether the signals being received, generally in the form of successive symbols or information bits, are interdependent. Signals received from, for example, a convolutional encoder, may be interdependent signals, that is, signals with memory. In this regard, a convolutional encoder may generate NRZI or continuous-phase modulation (CPM), which is generally based on a finite state machine operation.
One method or algorithm for signal detection in a receiver system that decodes convolutional encoded data is maximum-likelihood sequence detection or estimation (MLSE). The MLSE is an algorithm that performs soft decisions while searching for a sequence that minimizes a distance metric in a trellis that characterizes the memory or interdependence of the transmitted signal. In this regard, an operation based on the Viterbi algorithm may be utilized to reduce the number of sequences in the trellis search when new signals are received.
Another method or algorithm for signal detection of convolutional encoded data that makes symbol-by-symbol decisions is maximum a posteriori probability (MAP). The optimization of the MAP algorithm is based on minimizing the probability of a symbol error. In many instances, the MAP algorithm may be difficult to implement because of its computational complexity.
The Viterbi algorithm may be utilized to perform the maximum likelihood decoding of convolutional codes. When a signal has no memory, a symbol-by-symbol detector may be utilized to minimize the probability of a symbol error. When a transmitted signal has memory, the signals transmitted in successive symbol intervals are interdependent. An optimum detector for a signal with memory may base its decisions on observation of a sequence of received signals over successive signal intervals. A maximum likelihood sequence detection algorithm may search for the minimum Euclidean distance path through a trellis that characterizes the memory in the transmitted signal.
Improvements in the design and implementation of optimized receivers for decoding convolutional encoded data may require modifications to the application of the MLSE algorithm, the Viterbi algorithm, and/or the MAP algorithm in accordance with the modulation method utilized in signal transmission.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of such systems with some aspects of the present invention as set forth in the remainder of the present application with reference to the drawings.